Missing Values

Correlations

Feature Correlations

Correlations to Target

Relation to target variable seems to be weak at best. But this may not be the right way to visualize. We should do histograms faceted by target

Automated Visualization

Modeling

https://github.com/pycaret/pycaret/blob/master/tutorials/Binary%20Classification%20Tutorial%20Level%20Beginner%20-%20%20CLF101.ipynb

Setup

Custom Metric

Baseline Model

Explainability

Inbuilt in PyCaret

Manually recreating PyCaret plots for Interpretibility

Partial Dependence Plots

https://towardsdatascience.com/explain-your-model-with-the-shap-values-bc36aac4de3d

Individual Observation Interpretibility

Let me describe this elegant plot in great detail:

Retrains on entire train dataset

Check final performance

Tune Best Model

XGBoost

Catboost (trial)

Conclusions

Logs